Search Results (13)

We model and describe the combined effect of a series of urban heat islands (UHIs), generated by nearby cities aligned as an archipelago, on the vertical diffusion of heat and the temperature structure in the lower atmosphere over an urban chain in northwestern Morocco. We use the Weather and Forecasting Model (WRF) coupled to an urban canopy model to run simulations during the northern summer. We show that when the land surface is characterized accurately, the WRF model can effectively resolve the scale of the urban archipelago effect and describe its detailed diurnal structure. Our results indicate that the combined effect of multiple UHIs in proximity is more impactful than the sum of their parts. Specifically, the urban archipelago’s effect alters the vertical temperature structure through upward diffusion of heat and extends its scale from local to meso-scale. This alters the wind pattern and may affect local weather conditions and air quality. These results underline the importance of considering the urban archipelago effect when studying urban climate. They also extend beyond academic research to offer valuable insights for urban planners in emphasizing the importance of urban typology and spatial proximity in city design and balancing cities’ interconnectivity with sustainable development and resilience. Full article

Resource conflicts constitute a major global issue in areas rich in natural resources. The modeling of factors influencing natural resource conflicts (NRCs), including environmental, health, socio-economic, political, and legal aspects, presents a significant challenge compounded by inadequate data. Quantitative research frequently emphasizes large-scale conflicts. This study presents a novel multilevel approach, SEFLAME-CM—Spatially Explicit Fuzzy Logic-Adapted Model for Conflict Management—for advancing understanding of the relationship between NRCs and drivers under territorial and rebel-based typologies at a community level. SEFLAME-CM is hypothesized to yield a more robust positive correlation between the risk of NRCs and the interacting conflict drivers, provided that the conflict drivers and input variables remain the same. Local knowledge from stakeholders is integrated into spatial decision-making tools to advance sustainable peace initiatives. We compared our model with spatial multi-criteria evaluation for conflict management (SMCE-CM) and spatial statistics. The results from the Moran’s I scatter plots of the overall conflicts of the SEFLAME-CM and SMCE-CM models exhibit substantial values of 0.99 and 0.98, respectively. Territorial resource violence due to environmental drivers increases coast-wards, more than that stemming from rebellion. Weighing fuzzy rules and conflict drivers enables equal comparison. Environmental variables, including proximity to arable land, mangrove ecosystems, polluted water, and oil infrastructures are key factors in NRCs. Conversely, socio-economic and political factors seem to be of lesser importance, contradicting prior research conclusions. In Third World nations, local communities emphasize food security and access to environmental services over local political matters amid competition for resources. The synergistic integration of fuzzy logic analysis and community perception to address sustainable peace while simultaneously connecting environmental and socio-economic factors is SEFLAME-CM’s contribution. This underscores the importance of a holistic approach to resource conflicts in communities and the dissemination of knowledge among specialists and local stakeholders in the sustainable management of resource disputes. The findings can inform national policies and international efforts in addressing the intricate underlying challenges while emphasizing the knowledge and needs of impacted communities. SEFLAME-CM, with improvements, proficiently illustrates the capacity to model intricate real-world issues. Full article

Focusing on the agricultural area of “Capo Due Rami” in Rome, this research aims to interpret the architectural features of the rural dwellings through a typological analysis. Drawing on data collected from direct surveys, historical records, cartographic materials, and documentary sources, the morphological and settlement evaluation of agricultural constructions refines traditional methods and techniques used in the analysis of residential models. Using specifically designed observation sheets, the study highlights how the reclamation and drainage works carried out predominantly between the 19th and 20th centuries in the area have influenced the typology of buildings and their relationship with the agricultural environment. The findings underscore that the morphotype of the dwellings in “Capo Due Rami” derives from the practical demands of agriculture and the functional requirements of rural life, incorporating targeted architectural solutions to address sanitary and environmental concerns. The observation sheets were designed to integrate qualitative indicators, drawing on previous investigative experiences in typological analysis. While adhering to established methodologies, they have been modified to reflect the cartographic and documentary data specific to “Capo Due Rami”. This approach has made it possible to highlight the distinctive features of the area, such as the proximity between buildings and reclamation canals. Full article

Ancient Andean agricultural landscapes have been the subject of a large number of archaeological and agro-ecological studies, which generally refer to regions with favourable environmental conditions or, in the case of arid and semi-arid environments, those with irrigation facilities. The aim of this article is to present and analyse the pre-Hispanic rain-fed farming systems widely represented in two adjacent regions of Bolivia’s arid and cold southern Altiplano. The search for archaeological agricultural areas combined aerial analysis and field surveys. Agro-ecological characterisation was based on historical and ethnographic studies of the region’s present-day populations. Despite their geographical proximity, similar environmental conditions, and same agropastoral way of life, the typology of cultivated areas developed in the southern altiplano differs significantly. Within this same framework of adaptation and resilience, the sectorisation of agricultural systems observed in these two regions reveals a regional productive specialisation that favoured internal exchanges and exchanges with other regions. These differences are related to two models of non-centralised, low-inequality societies—one strongly based on cohesion and the other characterised by greater fragmentation and social conflict—underlining the limits of strict environmental determinism in shaping agricultural landscapes. These results provide new food for thought in the debate on the use and value of rain-fed agricultural practices and more broadly on the diversity of adaptations by human societies in extreme and unstable environmental contexts. Full article

Stakeholder engagement is a central tenet for understanding and solving sustainability challenges. Given the existing stakeholder knowledge base and the fact that practitioners mostly focus on the engagement of high-power and salience stakeholders, the interests of low-power and vulnerable stakeholders are often manipulated. Therefore, this research is devoted to the engagement of low-power and vulnerable stakeholders. Grounded in the stakeholder theory and the results of two illustrations, we demonstrate how the physical proximity of vulnerable stakeholders influences salience patterns in a multi-stakeholder engagement context. The contribution of the study is the conceptualisation of proximity as a stakeholder attribute, in addition to power, legitimacy, and urgency, to help managers identify and appropriately engage with vulnerable stakeholders. Thus, we extend stakeholder typologies by incorporating proximity into the existing attribute model. The proposed model addresses the paradoxical nature of stakeholder salience and engagement theories and furthers the sustainability agenda. Full article

The seismicity of the National Capital Region (NCR) of India increased significantly over the last decade. Communities in the NCR face significant exposure to damaging seismic events, and the seismic risk arises not only from the region’s proximity to the Himalayan mountains, but also from the socioeconomic vulnerabilities in its communities and the current capacities of different localities to respond to and recover from any unforeseen large seismic event. GIS-based spatial distribution of exposure to seismic hazards (SH) can help decision-makers and authorities identify locations with populations at high seismic risk, and to prepare risk-mitigation plans. Socioeconomic vulnerability (SeV) studies serve as a basis for quantifying qualitative measures. For this purpose, in the present study, the hazard of place (HoP) model is used to assess SeV to seismic hazards in the NCR. Social indicators like age, gender, literacy, family size, built environment, etc., comprising a total of 36 variables, are used to assess a socioeconomic vulnerability index (SeVI) based on factor and principal component (PCA) analyses. Based on PCA, 20 variables were retained and grouped into four factors: socioeconomic status, employment status, building typology, and family size. Ground-motion parameters, estimated from probabilistic seismic hazard assessment, are integrated with the socioeconomic vulnerability index to quantify exposure to seismic hazards. The spatial distributions in the produced socioeconomic-vulnerability index and seismic–hazard–exposure maps highlight the critical areas. The results reveal that areas of low literacy, high unemployment, and poor housing condition show moderate-to-high vulnerability. The south-eastern region of the study area is assessed as a high-risk zone by an integrated SeV–SH risk matrix. The results of this study emphasize the importance of the socioeconomic vulnerability component of disaster risk–reduction programs, from a holistic perspective, for the areas with high seismicity. Full article

In the tropics, the domestic water supply depends principally on ecosystem services, including the regulation and purification of water by humid, dense tropical forests. The Yangambi Biosphere Reserve (YBR) landscape is situated within such forests in the Democratic Republic of Congo (DRC). Surprisingly, given its proximity to the Congo River, the YBR is confronted with water issues. As part of its ecosystem function, the landscape is expected to reduce deterioration of water quality. However, environmental consequences are increasing due to conversion of its dense forest into other types of land use/land cover (LULC) in response to human activities. It is therefore important to check how the physicochemical quality parameters of water resources are influenced by landscape parameters—and to know if the population can adapt to this water vulnerability. To do this, we analyzed the watershed typology (including morphometric and LULC characteristics) and the physical and chemical parameters of water within the principal watershed’s rivers. We also analyzed data from surveys and the Yangambi meteorological station. We found that some landscape indices related to LULC significantly influence water quality deterioration in Yangambi. On average, each person in the Yangambi landscape uses 29–43 liters of water per day. Unfortunately, this falls short of World Health Organization standards regarding some parameters. The best fitted simple linear regression model explains the variation in pH as a function of edge density of perturbed forest, edge density of crop land and patch density of dense forest up to 94%, 92% and 90%, respectively. While many researchers have identified the consequences of climate change and human activities on these water resources, the population is not well-equipped to deal with them. These results suggest that water management policies should consider the specificities of the Yangambi landscape in order to develop better mitigation strategies for a rational management of water resources in the YBR in the context of climate change. Full article

The paper is dedicated to solving the problem of optimal text classification in the area of automated detection of typology of texts. In conventional approaches to topicality-based text classification (including topic modeling), the number of clusters is to be set up by the scholar, and the optimal number of clusters, as well as the quality of the model that designates proximity of texts to each other, remain unresolved questions. We propose a novel approach to the automated definition of the optimal number of clusters that also incorporates an assessment of word proximity of texts, combined with text encoding model that is based on the system of sentence embeddings. Our approach combines Universal Sentence Encoder (USE) data pre-processing, agglomerative hierarchical clustering by Ward’s method, and the Markov stopping moment for optimal clustering. The preferred number of clusters is determined based on the “e-2” hypothesis. We set up an experiment on two datasets of real-world labeled data: News20 and BBC. The proposed model is tested against more traditional text representation methods, like bag-of-words and word2vec, to show that it provides a much better-resulting quality than the baseline DBSCAN and OPTICS models with different encoding methods. We use three quality metrics to demonstrate that clustering quality does not drop when the number of clusters grows. Thus, we get close to the convergence of text clustering and text classification. Full article

Road infrastructures represent a key point in the development of smart cities. In any case, the environmental impact of road traffic should be carefully assessed. Acoustic noise is one of the most important issues to be monitored by means of sound level measurements. When a large measurement campaign is not possible, road traffic noise predictive models (RTNMs) can be used. Standard RTNMs present in literature usually require in input several information about the traffic, such as flows of vehicles, percentage of heavy vehicles, average speed, etc. Many times, the lack of information about this large set of inputs is a limitation to the application of predictive models on a large scale. In this paper, a new methodology, easy to be implemented in a sensor concept, based on video processing and object detection tools, is proposed: the Equivalent Acoustic Level Estimator (EAgLE). The input parameters of EAgLE are detected analyzing video images of the area under study. Once the number of vehicles, the typology (light or heavy vehicle), and the speeds are recorded, the sound power level of each vehicle is computed, according to the EU recommended standard model (CNOSSOS-EU), and the Sound Exposure Level (SEL) of each transit is estimated at the receiver. Finally, summing up the contributions of all the vehicles, the continuous equivalent level, L_eq, on a given time range can be assessed. A preliminary test of the EAgLE technique is proposed in this paper on two sample measurements performed in proximity of an Italian highway. The results will show excellent performances in terms of agreement with the measured L_eq and comparing with other RTNMs. These satisfying results, once confirmed by a larger validation test, will open the way to the development of a dedicated sensor, embedding the EAgLE model, with possible interesting applications in smart cities and road infrastructures monitoring. These sites, in fact, are often equipped (or can be equipped) with a network of monitoring video cameras for safety purposes or for fining/tolling, that, once the model is properly calibrated and validated, can be turned in a large scale network of noise estimators. Full article

The present study examines the role of typological proximity in the acquisition of Differential Object Marking (DOM) in Spanish among eighteen (n = 18) Mandarin-speaking second language (L2) learners and sixteen (n = 16) Spanish heritage speakers (HSs) with Brazilian Portuguese (BP) as their dominant language. Specifically, we investigate the extent to which language proximity (languages are members of the same family) plays a role in the complete specification of the relevant features constraining DOM marking in Spanish. Results from an elicited production task and an acceptability judgment task (AJT) showed no support for the typological proximity model (Rothman 2010). There were also no age of onset of acquisition effects, in contrast to what was expected. The post-puberty Mandarin L2 learners outperformed the BP HSs in most of the conditions examined, suggesting a role for language instruction. Results are discussed along the lines of Liceras and Alba de la Fuente’s (2015) proposal whereby the locus of transfer is more related to the typological similarity between the languages at the microparametric level than to language proximity itself. Full article

The article attempts to provide a theoretical discussion on territorial governance by presenting both the neo-institutionalist position and the De Sousa Santos’ alternative models, with a view of highlighting the dimensions that can be relevant to understanding the territorial dynamics of Local Agro-food Systems (LAFS). The paper aims to build up a system of indicators, structured in four dimensions, concerning the territorial governance of LAFS: (i) multi-level coordination; (ii) democratic participation and accountability; (iii) cooperation among producers and other stakeholders and (iv) relationships with the environment. We verify, as a hypothesis, that the typology of markets to which the identity-based products are directed plays a decisive role in the way that processes of territorial governance of LAFS are constructed. The results of an empirical research, developed in four LAFS in Mexico, are presented: prickly pear cactus in Morelos, blackberry in Michoacán, cuitlacoche (corn smut) in Tlaxcala and coffee in Veracruz. Two types of territorial governance of LAFS may be distinguished: those that can be strengthened by the geographical and organisational proximity of the markets and the action of local stakeholders and governments—prickly pear cactus and cuitlacoche—versus those which are devoted to export and are conducted by large companies in which marketing networks involve certification mechanisms and a large number of institutions—coffee and blackberry. Full article

This study examines the role of previously known language in L3 Brazilian Portuguese (BP) object expression acquisition. It investigates the claims of the main models of L3 transfer, the cumulative enhancement model (CEM) (Flynn et al. 2004), the L2 status factor (Bardel and Falk 2007) and the typological proximity model (TPM) (Rothman 2011) in both comprehension and production tasks. It also aims at measuring the extent of transfer effects in comprehension and production. Participants (N = 33) were divided into three groups, a mirror image group of L3 BP learners who already knew English and Spanish, and a native control group. They performed a self-paced reading task and a story telling task, which focused on object clitics in BP. Results indicate early convergence to the BP grammar by the L3 learners in what refers to object expression. They also suggest that, although no major effects of transfer were obtained, clitic placement errors in the production task and preference for inanimate and non-specific contexts for null objects can be traced to Spanish, independent of order of acquisition, providing evidence in favor of the TPM. Finally, comprehension seems to override the effects of language transfer earlier than production. Full article

Cities are traditionally considered as centers of prosperity, but after a long process of deindustrialization, the classical opportunities presented by cities as administrative, production, financial and cultural hot spots can no longer be taken for granted without questioning the present organizational and spatial models. After an introduction to the decision-aid tools and processes needed to orient development in a sustainable way, the paper describes the characteristics and an application of the decision-aid tool created for analysis, diagnosis and evaluation of opportunities. The proposal briefly considers the reconnection of the city with its region, urban renewal, creative and productive activities, necessary support institutions, contemporary sustainable economic approaches and infrastructure. This approach is illustrated on the case of the incubator proposal for the City of Rijeka, Croatia, once an important port and industrial city with a long history. The technological modifications in the functioning of the port and abandoning of industrial production in the proximity, but also geological formation and prevalent building typologies, make the case exemplary of the problems faced in contemporary cities. The paper proposes a process and tools for analysis and evaluation and indicators for the sustainability of the proposal. Full article